Optimization Decision Study of Business Smart Building Clusters Considering Shared Energy Storage

Wenhui Zhao, Shuting Xu () and Peng Guo
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Wenhui Zhao: School of Economics and Management, Shanghai University of Electric Power, Shanghai 201306, China
Shuting Xu: School of Economics and Management, Shanghai University of Electric Power, Shanghai 201306, China
Peng Guo: Shanghai Qiyuan Green Power Technology Co., Ltd., Shanghai 200010, China

Sustainability, 2024, vol. 16, issue 8, 1-14

Abstract: Smart buildings have a large number of dispatchable resources, both for power production and consumption functions, and the energy consumption of intelligent building clusters has a good complementary and interactive relationship, which can better promote the local consumption of distributed energy. In order to realize the goal of “dual-carbon” and promote the construction of a new power system mainly based on renewable energy, this paper takes the Business Smart Building (BSB) cluster with photovoltaic (PV) power generation as the research object. A peer-to-peer (P2P) energy trading model with shared energy storage (SES) for BSBs is constructed, and the potential risk of the stochastic volatility of photovoltaic power generation to BSBs is evaluated using conditional value-at-risk (CVaR). Finally, the optimal strategy for P2P energy sharing among BSBs is obtained by distributed solving using the alternating direction multiplier method (ADMM). The results show that the proposed model can minimize the operating cost of the multi-BSB alliance and realize win–win benefits for building users and shared energy storage operators. Meanwhile, the proposed CVaR gives a trade-off between benefits and risks, which can satisfy the needs of decision-makers with different risk preferences in making decisions.

Keywords: business smart building (BSB); shared energy storage (SES); P2P energy trading model; conditional value-at-risk (CVaR) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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